Embodiments are directed to a method for securely performing biometric authentication online. The method described can be used to securely perform biometric authentication on a mobile device. For protecting the privacy of the users biometric data, a cryptographic comparison protocol can be used to perform matching of encrypted templates. For example, the cryptographic comparison protocol may involve Fuzzy Extractors (FE), Homomorphic Encryption (HE), and/or Secure Multi-Party Computation (SMPC).

This disclosure describes techniques for authenticating one or more devices of a user in association with cloud computing services. The techniques include generating credential portions. The credential portions may be used in a signing protocol between one of the user devices and a cloud authenticator. The signing protocol may generate a signature that may be used in authentication with a cloud computing service. In some cases, the credential portions may be shared with other devices of the user. As such, the cloud authenticate may assist multiple user devices to authenticate with the cloud computing service.

A multiparty computing system includes at least a first compute node and a second compute node, each of the first compute node and the second compute node each configured to execute a multiparty computation. The first compute node is configured to perform first operations of the multiparty computation over a share of first secret data and a share of second secret data; detect a checkpoint event; and, in response to detection of the checkpoint event, save a state of the multiparty computation on the first compute node to a checkpoint storage. In response to detection of a resume event, the first compute node executes a resume protocol with the second compute node, where the resume protocol includes exchanging messages with the second compute node, and determining, based on the messages, an operation in the multiparty computation to be the starting point to resume the multiparty computation.

Method for determining an extremum based on secure multi-party computation includes: acquiring a t.sup.th mean obtained in t.sup.th round federated computation; performing (t+1).sup.th round federated computation based on valid node data of an i.sup.th node device in response to the valid node data of the i.sup.th node device being greater than the t.sup.th mean; performing the (t+1).sup.th round federated computation based on invalid node data in response to the valid node data of the i.sup.th node device being less than or equal to the t.sup.th mean; and determining that the valid node data of the i.sup.th node device is the extremum in response to the valid node data of the i.sup.th node device being greater than or equal to an (n−1).sup.th mean after (n−1).sup.th round federated computation.

Provided are systems for conducting private set intersection (PSI) techniques with multiple parties using a data repository that include at least one processor to generate a data repository, receive, from a submission entity system associated with a submission entity, a private set intersection (PSI) data query that includes a match parameter for performing the PSI data query, transmit, to the submission entity system, a data classification encryption key, wherein the data classification encryption key is associated with a data field that corresponds to a match parameter data field of the match parameter, determine whether to authorize the PSI data query on the data repository, transmit, to the submission entity system, a data authorization encryption key based on determining to authorize the PSI data query on the data repository, and perform the PSI data query on the data repository. Methods and computer program products are also provided.

Methods, systems, and apparatus, including a method for determining network measurements. In some aspects, a method includes receiving, by a first aggregation server and from each of multiple client devices, encrypted impression data. A second aggregation server receives, from each of at least a portion of the multiple client devices, encrypted conversion data. The first aggregation server and the second aggregation server perform a multi-party computation process to generate chronological sequences of encrypted impression data and encrypted conversion data and to decrypt the encrypted impression data and the encrypted conversion data.

Provided are a training method and apparatus for a distributed machine learning model, a device and a medium. The training method includes: acquiring a first homomorphic encryption intermediate parameter and a second homomorphic encryption intermediate parameter; generating a first interference parameter, and forming a first encryption interference parameter by encrypting the first interference parameter by using a second homomorphic public key of a second participant; performing calculation based on the first homomorphic encryption intermediate parameter, the second homomorphic encryption intermediate parameter, the first encryption interference parameter and the homomorphic calculation function of a first submodel to generate a first encryption key parameter.

A method is presented for secure determination of a solution (S) to a computational task by a pooled resource or group having a plurality of participants (P), the group operating in a trust-less, or dealer-free, system or manner. Access to a resource or reward is offered in exchange for the solution. Individuals generate their own key pair and use their public key to establish with the group an initial shared public key that they can all use to find a solution to the task. The resource or reward can be secured by the verified shared public key. Because the private keys of each participant were used in the determination of the initial shared public key that lead to the solution then participants must then collaborate to unlock the resource or reward because the corresponding shared private key can only be generated by all participants or a pre-agreed threshold of participants.

A method and device for establishing a communication along a communications channel between a first device (200A) and a second device (200B) is disclosed. The method comprises mutually discovering the first device (200A) and the second device (200B), validating (F5, F6, F7) the communications channel between the first device (200A) and the second device (200B) by exchange of data messages, exchanging a secret between the first device (200A) and the second device (200B) and then exchanging encrypted messages along the communications channel.

The present invention relates to methods for secure computation and/or communication Entangled photons (118) are generated such that each participating party receives a series of optical pulses. Each party has private information (110, 112) which are ever transmitted through public or private communication channels Instead, each party converts their respective private information (110, 112) into measurement bases via an encryption process (114, 116) which are then applied to the entangled photons (118). After the measurement process, e.g., quantum frequency conversion (122, 124), reference indices are announced (124, 126) so that computation can be performed (128) without revealing the private information directly or indirectly.